The third category is related to our work is exploration based on information gain [1]}. Information gain is generally comprehended as the intrinsic reward of agents, which can measure the contribution of a new state to information. To reach a state where more rewards can be obtained, an agent selects the actions of maximizing empowerment that is calculated by mutual information [2]}. If a set of states share the same optimal action, then the action can be interpreted as a representation of the states. There is another approach [3]} also uses mutual information as an exploration reward. If a set of states share the same optimal action, then the action can be considered as a representation of states. The goal is to find the action with the most state information among the strategies which has uniform rewards. That is, It needs to minimize the mutual information of actions and the states.
